{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6d6dc73f",
   "metadata": {},
   "source": [
    "# 环境准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "70c82038",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple\n",
      "Requirement already satisfied: appnope==0.1.4 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 1)) (0.1.4)\n",
      "Requirement already satisfied: asttokens==3.0.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 2)) (3.0.0)\n",
      "Requirement already satisfied: beautifulsoup4==4.13.4 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 3)) (4.13.4)\n",
      "Requirement already satisfied: certifi==2025.4.26 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 4)) (2025.4.26)\n",
      "Requirement already satisfied: cffi==1.17.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 5)) (1.17.1)\n",
      "Requirement already satisfied: charset-normalizer==3.4.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 6)) (3.4.2)\n",
      "Requirement already satisfied: comm==0.2.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 7)) (0.2.2)\n",
      "Requirement already satisfied: contourpy==1.3.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 8)) (1.3.2)\n",
      "Requirement already satisfied: cryptography==45.0.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 9)) (45.0.3)\n",
      "Requirement already satisfied: curl_cffi==0.11.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 10)) (0.11.1)\n",
      "Requirement already satisfied: cycler==0.12.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 11)) (0.12.1)\n",
      "Requirement already satisfied: debugpy==1.8.14 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 12)) (1.8.14)\n",
      "Requirement already satisfied: decorator==5.2.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 13)) (5.2.1)\n",
      "Requirement already satisfied: executing==2.2.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 14)) (2.2.0)\n",
      "Requirement already satisfied: fonttools==4.58.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 15)) (4.58.0)\n",
      "Requirement already satisfied: frozendict==2.4.6 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 16)) (2.4.6)\n",
      "Requirement already satisfied: idna==3.10 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 17)) (3.10)\n",
      "Requirement already satisfied: inflection==0.5.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 18)) (0.5.1)\n",
      "Requirement already satisfied: ipykernel==6.29.5 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 19)) (6.29.5)\n",
      "Requirement already satisfied: ipython==9.2.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 20)) (9.2.0)\n",
      "Requirement already satisfied: ipython_pygments_lexers==1.1.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 21)) (1.1.1)\n",
      "Requirement already satisfied: jedi==0.19.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 22)) (0.19.2)\n",
      "Requirement already satisfied: jupyter_client==8.6.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 23)) (8.6.3)\n",
      "Requirement already satisfied: jupyter_core==5.8.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 24)) (5.8.1)\n",
      "Requirement already satisfied: kiwisolver==1.4.8 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 25)) (1.4.8)\n",
      "Requirement already satisfied: matplotlib==3.10.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 26)) (3.10.3)\n",
      "Requirement already satisfied: matplotlib-inline==0.1.7 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 27)) (0.1.7)\n",
      "Requirement already satisfied: more-itertools==10.7.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 28)) (10.7.0)\n",
      "Requirement already satisfied: multitasking==0.0.11 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 29)) (0.0.11)\n",
      "Requirement already satisfied: Nasdaq-Data-Link==1.0.4 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 30)) (1.0.4)\n",
      "Requirement already satisfied: nest-asyncio==1.6.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 31)) (1.6.0)\n",
      "Requirement already satisfied: numpy==2.2.6 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 32)) (2.2.6)\n",
      "Requirement already satisfied: packaging==25.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 33)) (25.0)\n",
      "Requirement already satisfied: pandas==2.2.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 34)) (2.2.3)\n",
      "Requirement already satisfied: parso==0.8.4 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 35)) (0.8.4)\n",
      "Requirement already satisfied: peewee==3.18.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 36)) (3.18.1)\n",
      "Requirement already satisfied: pexpect==4.9.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 37)) (4.9.0)\n",
      "Requirement already satisfied: pillow==11.2.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 38)) (11.2.1)\n",
      "Requirement already satisfied: platformdirs==4.3.8 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 39)) (4.3.8)\n",
      "Requirement already satisfied: prompt_toolkit==3.0.51 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 40)) (3.0.51)\n",
      "Requirement already satisfied: protobuf==6.31.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 41)) (6.31.0)\n",
      "Requirement already satisfied: psutil==7.0.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 42)) (7.0.0)\n",
      "Requirement already satisfied: ptyprocess==0.7.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 43)) (0.7.0)\n",
      "Requirement already satisfied: pure_eval==0.2.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 44)) (0.2.3)\n",
      "Requirement already satisfied: pycparser==2.22 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 45)) (2.22)\n",
      "Requirement already satisfied: Pygments==2.19.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 46)) (2.19.1)\n",
      "Requirement already satisfied: pyparsing==3.2.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 47)) (3.2.3)\n",
      "Requirement already satisfied: PySock==0.3.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 48)) (0.3.2)\n",
      "Requirement already satisfied: PySocks==1.7.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 49)) (1.7.1)\n",
      "Requirement already satisfied: python-dateutil==2.9.0.post0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 50)) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz==2025.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 51)) (2025.2)\n",
      "Requirement already satisfied: PyYAML==6.0.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 52)) (6.0.2)\n",
      "Requirement already satisfied: pyzmq==26.4.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 53)) (26.4.0)\n",
      "Requirement already satisfied: requests==2.32.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 54)) (2.32.3)\n",
      "Requirement already satisfied: six==1.17.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 55)) (1.17.0)\n",
      "Requirement already satisfied: soupsieve==2.7 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 56)) (2.7)\n",
      "Requirement already satisfied: stack-data==0.6.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 57)) (0.6.3)\n",
      "Requirement already satisfied: tornado==6.5.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 58)) (6.5.1)\n",
      "Requirement already satisfied: traitlets==5.14.3 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 59)) (5.14.3)\n",
      "Requirement already satisfied: typing_extensions==4.13.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 60)) (4.13.2)\n",
      "Requirement already satisfied: tzdata==2025.2 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 61)) (2025.2)\n",
      "Requirement already satisfied: urllib3==2.4.0 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 62)) (2.4.0)\n",
      "Requirement already satisfied: wcwidth==0.2.13 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 63)) (0.2.13)\n",
      "Requirement already satisfied: websockets==15.0.1 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 64)) (15.0.1)\n",
      "Requirement already satisfied: yfinance==0.2.61 in /Users/songdragon/.pyenv/versions/mp_py/lib/python3.13/site-packages (from -r requirements.txt (line 65)) (0.2.61)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install -r requirements.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7f29c64",
   "metadata": {},
   "source": [
    "## 准备Nasdaq Data Link\n",
    "Quandl已经自动重定向到Nasda Data Link，注册账号，参考：[Get Financial Data Directly Into Python](https://data.nasdaq.com/tools/python)设置api key。\n",
    "\n",
    "### 方式一 使用Local API Key file (推荐)\n",
    "``` python\n",
    "nasdaqdatalink.read_key(filename=\"~/.nasdaq/data_link_apikey\")\n",
    "```\n",
    "\n",
    "### 方式二 使用Local API Kye Environment Viariable\n",
    "```shell\n",
    "export NASDAQ_DATA_LINK_API_KEY=AAA\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "21ac1985",
   "metadata": {},
   "outputs": [
    {
     "ename": "DataLinkError",
     "evalue": "(Status 403) Something went wrong. Please try again. If you continue to have problems, please contact us at connect@data.nasdaq.com.",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mJSONDecodeError\u001b[39m                           Traceback (most recent call last)",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/requests/models.py:974\u001b[39m, in \u001b[36mResponse.json\u001b[39m\u001b[34m(self, **kwargs)\u001b[39m\n\u001b[32m    973\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m974\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcomplexjson\u001b[49m\u001b[43m.\u001b[49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mtext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    975\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m    976\u001b[39m     \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[32m    977\u001b[39m     \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m/usr/local/Cellar/python@3.13/3.13.3_1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/json/__init__.py:346\u001b[39m, in \u001b[36mloads\u001b[39m\u001b[34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[39m\n\u001b[32m    343\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[32m    344\u001b[39m         parse_int \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m parse_float \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[32m    345\u001b[39m         parse_constant \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_pairs_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kw):\n\u001b[32m--> \u001b[39m\u001b[32m346\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_default_decoder\u001b[49m\u001b[43m.\u001b[49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    347\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[36mFile \u001b[39m\u001b[32m/usr/local/Cellar/python@3.13/3.13.3_1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/json/decoder.py:345\u001b[39m, in \u001b[36mJSONDecoder.decode\u001b[39m\u001b[34m(self, s, _w)\u001b[39m\n\u001b[32m    341\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[32m    342\u001b[39m \u001b[33;03mcontaining a JSON document).\u001b[39;00m\n\u001b[32m    343\u001b[39m \n\u001b[32m    344\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m345\u001b[39m obj, end = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[43m=\u001b[49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    346\u001b[39m end = _w(s, end).end()\n",
      "\u001b[36mFile \u001b[39m\u001b[32m/usr/local/Cellar/python@3.13/3.13.3_1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/json/decoder.py:363\u001b[39m, in \u001b[36mJSONDecoder.raw_decode\u001b[39m\u001b[34m(self, s, idx)\u001b[39m\n\u001b[32m    362\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[32m--> \u001b[39m\u001b[32m363\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m JSONDecodeError(\u001b[33m\"\u001b[39m\u001b[33mExpecting value\u001b[39m\u001b[33m\"\u001b[39m, s, err.value) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m    364\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m obj, end\n",
      "\u001b[31mJSONDecodeError\u001b[39m: Expecting value: line 1 column 1 (char 0)",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[31mJSONDecodeError\u001b[39m                           Traceback (most recent call last)",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/connection.py:90\u001b[39m, in \u001b[36mConnection.parse\u001b[39m\u001b[34m(cls, response)\u001b[39m\n\u001b[32m     89\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m---> \u001b[39m\u001b[32m90\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mresponse\u001b[49m\u001b[43m.\u001b[49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     91\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m:\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/requests/models.py:978\u001b[39m, in \u001b[36mResponse.json\u001b[39m\u001b[34m(self, **kwargs)\u001b[39m\n\u001b[32m    975\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m    976\u001b[39m     \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[32m    977\u001b[39m     \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m978\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m RequestsJSONDecodeError(e.msg, e.doc, e.pos)\n",
      "\u001b[31mJSONDecodeError\u001b[39m: Expecting value: line 1 column 1 (char 0)",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[31mDataLinkError\u001b[39m                             Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 6\u001b[39m\n\u001b[32m      3\u001b[39m nasdaqdatalink.read_key(filename=\u001b[33m\"\u001b[39m\u001b[33m~/.nasdaq/data_link_apikey\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m      4\u001b[39m \u001b[38;5;66;03m#print(nasdaqdatalink.ApiConfig.api_key)\u001b[39;00m\n\u001b[32m      5\u001b[39m \u001b[38;5;66;03m# 需要购买数据集\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m6\u001b[39m mydata = \u001b[43mnasdaqdatalink\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mFRED/GDP\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m      7\u001b[39m \u001b[38;5;28mprint\u001b[39m(mydata.head())\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/get.py:48\u001b[39m, in \u001b[36mget\u001b[39m\u001b[34m(dataset, **kwargs)\u001b[39m\n\u001b[32m     46\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m dataset_args[\u001b[33m'\u001b[39m\u001b[33mcolumn_index\u001b[39m\u001b[33m'\u001b[39m] \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[32m     47\u001b[39m         kwargs.update({\u001b[33m'\u001b[39m\u001b[33mcolumn_index\u001b[39m\u001b[33m'\u001b[39m: dataset_args[\u001b[33m'\u001b[39m\u001b[33mcolumn_index\u001b[39m\u001b[33m'\u001b[39m]})\n\u001b[32m---> \u001b[39m\u001b[32m48\u001b[39m     data = \u001b[43mDataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdataset_args\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mcode\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m=\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhandle_column_not_found\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[32m     49\u001b[39m \u001b[38;5;66;03m# Array\u001b[39;00m\n\u001b[32m     50\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(dataset, \u001b[38;5;28mlist\u001b[39m):\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/model/dataset.py:47\u001b[39m, in \u001b[36mDataset.data\u001b[39m\u001b[34m(self, **options)\u001b[39m\n\u001b[32m     45\u001b[39m updated_options = Util.merge_options(\u001b[33m'\u001b[39m\u001b[33mparams\u001b[39m\u001b[33m'\u001b[39m, params, **options)\n\u001b[32m     46\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m---> \u001b[39m\u001b[32m47\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mData\u001b[49m\u001b[43m.\u001b[49m\u001b[43mall\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mupdated_options\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     48\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m NotFoundError:\n\u001b[32m     49\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m handle_not_found_error:\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/operations/list.py:15\u001b[39m, in \u001b[36mListOperation.all\u001b[39m\u001b[34m(cls, **options)\u001b[39m\n\u001b[32m     13\u001b[39m     options[\u001b[33m'\u001b[39m\u001b[33mparams\u001b[39m\u001b[33m'\u001b[39m] = {}\n\u001b[32m     14\u001b[39m path = Util.constructed_path(\u001b[38;5;28mcls\u001b[39m.list_path(), options[\u001b[33m'\u001b[39m\u001b[33mparams\u001b[39m\u001b[33m'\u001b[39m])\n\u001b[32m---> \u001b[39m\u001b[32m15\u001b[39m r = \u001b[43mConnection\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mget\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     16\u001b[39m response_data = r.json()\n\u001b[32m     17\u001b[39m Util.convert_to_dates(response_data)\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/connection.py:40\u001b[39m, in \u001b[36mConnection.request\u001b[39m\u001b[34m(cls, http_verb, url, **options)\u001b[39m\n\u001b[32m     36\u001b[39m options[\u001b[33m'\u001b[39m\u001b[33mheaders\u001b[39m\u001b[33m'\u001b[39m] = headers\n\u001b[32m     38\u001b[39m abs_url = \u001b[33m'\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m/\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m'\u001b[39m % (ApiConfig.api_base, url)\n\u001b[32m---> \u001b[39m\u001b[32m40\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mexecute_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhttp_verb\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mabs_url\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/connection.py:52\u001b[39m, in \u001b[36mConnection.execute_request\u001b[39m\u001b[34m(cls, http_verb, url, **options)\u001b[39m\n\u001b[32m     47\u001b[39m response = session.request(method=http_verb,\n\u001b[32m     48\u001b[39m                            url=url,\n\u001b[32m     49\u001b[39m                            verify=ApiConfig.verify_ssl,\n\u001b[32m     50\u001b[39m                            **options)\n\u001b[32m     51\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m response.status_code < \u001b[32m200\u001b[39m \u001b[38;5;129;01mor\u001b[39;00m response.status_code >= \u001b[32m300\u001b[39m:\n\u001b[32m---> \u001b[39m\u001b[32m52\u001b[39m     \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mhandle_api_error\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresponse\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     53\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m     54\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m response\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/connection.py:96\u001b[39m, in \u001b[36mConnection.handle_api_error\u001b[39m\u001b[34m(cls, resp)\u001b[39m\n\u001b[32m     94\u001b[39m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[32m     95\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mhandle_api_error\u001b[39m(\u001b[38;5;28mcls\u001b[39m, resp):\n\u001b[32m---> \u001b[39m\u001b[32m96\u001b[39m     error_body = \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mparse\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresp\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     98\u001b[39m     \u001b[38;5;66;03m# if our app does not form a proper data_link_error response\u001b[39;00m\n\u001b[32m     99\u001b[39m     \u001b[38;5;66;03m# throw generic error\u001b[39;00m\n\u001b[32m    100\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m'\u001b[39m\u001b[33mquandl_error\u001b[39m\u001b[33m'\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m error_body:\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/.pyenv/versions/mp_py/lib/python3.13/site-packages/nasdaqdatalink/connection.py:92\u001b[39m, in \u001b[36mConnection.parse\u001b[39m\u001b[34m(cls, response)\u001b[39m\n\u001b[32m     90\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m response.json()\n\u001b[32m     91\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m:\n\u001b[32m---> \u001b[39m\u001b[32m92\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m DataLinkError(http_status=response.status_code, http_body=response.text)\n",
      "\u001b[31mDataLinkError\u001b[39m: (Status 403) Something went wrong. Please try again. If you continue to have problems, please contact us at connect@data.nasdaq.com."
     ]
    }
   ],
   "source": [
    "'''验证读取apikey'''\n",
    "import nasdaqdatalink\n",
    "nasdaqdatalink.read_key(filename=\"~/.nasdaq/data_link_apikey\")\n",
    "#print(nasdaqdatalink.ApiConfig.api_key)\n",
    "# 需要购买数据集\n",
    "mydata = nasdaqdatalink.get(\"FRED/GDP\")\n",
    "print(mydata.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fef82ca1",
   "metadata": {},
   "source": [
    "## 准备yfinance/tushare/akshare\n",
    "因为nasdaq data link需要购买数据集权限，因此切换为免费的接口获取数据，可以选择：yfinance、tushare、akshare。\n",
    "\n",
    "### yfinance\n",
    "参考：https://ranaroussi.github.io/yfinance/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76d435c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'address1': 'One Apple Park Way',\n",
       " 'city': 'Cupertino',\n",
       " 'state': 'CA',\n",
       " 'zip': '95014',\n",
       " 'country': 'United States',\n",
       " 'phone': '(408) 996-1010',\n",
       " 'website': 'https://www.apple.com',\n",
       " 'industry': 'Consumer Electronics',\n",
       " 'industryKey': 'consumer-electronics',\n",
       " 'industryDisp': 'Consumer Electronics',\n",
       " 'sector': 'Technology',\n",
       " 'sectorKey': 'technology',\n",
       " 'sectorDisp': 'Technology',\n",
       " 'longBusinessSummary': 'Apple Inc. designs, manufactures, and markets smartphones, personal computers, tablets, wearables, and accessories worldwide. The company offers iPhone, a line of smartphones; Mac, a line of personal computers; iPad, a line of multi-purpose tablets; and wearables, home, and accessories comprising AirPods, Apple TV, Apple Watch, Beats products, and HomePod. It also provides AppleCare support and cloud services; and operates various platforms, including the App Store that allow customers to discover and download applications and digital content, such as books, music, video, games, and podcasts, as well as advertising services include third-party licensing arrangements and its own advertising platforms. In addition, the company offers various subscription-based services, such as Apple Arcade, a game subscription service; Apple Fitness+, a personalized fitness service; Apple Music, which offers users a curated listening experience with on-demand radio stations; Apple News+, a subscription news and magazine service; Apple TV+, which offers exclusive original content; Apple Card, a co-branded credit card; and Apple Pay, a cashless payment service, as well as licenses its intellectual property. The company serves consumers, and small and mid-sized businesses; and the education, enterprise, and government markets. It distributes third-party applications for its products through the App Store. The company also sells its products through its retail and online stores, and direct sales force; and third-party cellular network carriers, wholesalers, retailers, and resellers. Apple Inc. was founded in 1976 and is headquartered in Cupertino, California.',\n",
       " 'fullTimeEmployees': 164000,\n",
       " 'companyOfficers': [{'maxAge': 1,\n",
       "   'name': 'Mr. Timothy D. Cook',\n",
       "   'age': 63,\n",
       "   'title': 'CEO & Director',\n",
       "   'yearBorn': 1961,\n",
       "   'fiscalYear': 2024,\n",
       "   'totalPay': 16520856,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Mr. Jeffrey E. Williams',\n",
       "   'age': 60,\n",
       "   'title': 'Chief Operating Officer',\n",
       "   'yearBorn': 1964,\n",
       "   'fiscalYear': 2024,\n",
       "   'totalPay': 5020737,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Ms. Katherine L. Adams',\n",
       "   'age': 60,\n",
       "   'title': 'Senior VP, General Counsel & Secretary',\n",
       "   'yearBorn': 1964,\n",
       "   'fiscalYear': 2024,\n",
       "   'totalPay': 5022182,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': \"Ms. Deirdre  O'Brien\",\n",
       "   'age': 57,\n",
       "   'title': 'Chief People Officer & Senior VP of Retail',\n",
       "   'yearBorn': 1967,\n",
       "   'fiscalYear': 2024,\n",
       "   'totalPay': 5022182,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Mr. Kevan  Parekh',\n",
       "   'age': 52,\n",
       "   'title': 'Senior VP & CFO',\n",
       "   'yearBorn': 1972,\n",
       "   'fiscalYear': 2024,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Mr. Chris  Kondo',\n",
       "   'title': 'Senior Director of Corporate Accounting',\n",
       "   'fiscalYear': 2024,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Suhasini  Chandramouli',\n",
       "   'title': 'Director of Investor Relations',\n",
       "   'fiscalYear': 2024,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Ms. Kristin Huguet Quayle',\n",
       "   'title': 'Vice President of Worldwide Communications',\n",
       "   'fiscalYear': 2024,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Mr. Greg  Joswiak',\n",
       "   'title': 'Senior Vice President of Worldwide Marketing',\n",
       "   'fiscalYear': 2024,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0},\n",
       "  {'maxAge': 1,\n",
       "   'name': 'Mr. Adrian  Perica',\n",
       "   'age': 50,\n",
       "   'title': 'Vice President of Corporate Development',\n",
       "   'yearBorn': 1974,\n",
       "   'fiscalYear': 2024,\n",
       "   'exercisedValue': 0,\n",
       "   'unexercisedValue': 0}],\n",
       " 'auditRisk': 7,\n",
       " 'boardRisk': 1,\n",
       " 'compensationRisk': 3,\n",
       " 'shareHolderRightsRisk': 1,\n",
       " 'overallRisk': 1,\n",
       " 'governanceEpochDate': 1746057600,\n",
       " 'compensationAsOfEpochDate': 1735603200,\n",
       " 'irWebsite': 'http://investor.apple.com/',\n",
       " 'executiveTeam': [],\n",
       " 'maxAge': 86400,\n",
       " 'priceHint': 2,\n",
       " 'previousClose': 200.21,\n",
       " 'open': 200.68,\n",
       " 'dayLow': 199.9,\n",
       " 'dayHigh': 202.73,\n",
       " 'regularMarketPreviousClose': 200.21,\n",
       " 'regularMarketOpen': 200.68,\n",
       " 'regularMarketDayLow': 199.9,\n",
       " 'regularMarketDayHigh': 202.73,\n",
       " 'dividendRate': 1.04,\n",
       " 'dividendYield': 0.52,\n",
       " 'exDividendDate': 1747008000,\n",
       " 'payoutRatio': 0.1558,\n",
       " 'fiveYearAvgDividendYield': 0.57,\n",
       " 'beta': 1.275,\n",
       " 'trailingPE': 31.266771,\n",
       " 'forwardPE': 24.11793,\n",
       " 'volume': 43425800,\n",
       " 'regularMarketVolume': 43425800,\n",
       " 'averageVolume': 62197668,\n",
       " 'averageVolume10days': 52256420,\n",
       " 'averageDailyVolume10Day': 52256420,\n",
       " 'bid': 190.44,\n",
       " 'ask': 210.62,\n",
       " 'bidSize': 1,\n",
       " 'askSize': 1,\n",
       " 'marketCap': 2993433083904,\n",
       " 'fiftyTwoWeekLow': 169.21,\n",
       " 'fiftyTwoWeekHigh': 260.1,\n",
       " 'priceToSalesTrailing12Months': 7.4767413,\n",
       " 'fiftyDayAverage': 205.9428,\n",
       " 'twoHundredDayAverage': 225.8192,\n",
       " 'trailingAnnualDividendRate': 1.0,\n",
       " 'trailingAnnualDividendYield': 0.004994755,\n",
       " 'currency': 'USD',\n",
       " 'tradeable': False,\n",
       " 'enterpriseValue': 3043126149120,\n",
       " 'profitMargins': 0.24301,\n",
       " 'floatShares': 14911480604,\n",
       " 'sharesOutstanding': 14935799808,\n",
       " 'sharesShort': 105169332,\n",
       " 'sharesShortPriorMonth': 113127198,\n",
       " 'sharesShortPreviousMonthDate': 1744675200,\n",
       " 'dateShortInterest': 1747267200,\n",
       " 'sharesPercentSharesOut': 0.0069999998,\n",
       " 'heldPercentInsiders': 0.02085,\n",
       " 'heldPercentInstitutions': 0.62839,\n",
       " 'shortRatio': 1.97,\n",
       " 'shortPercentOfFloat': 0.0069999998,\n",
       " 'impliedSharesOutstanding': 14949300224,\n",
       " 'bookValue': 4.471,\n",
       " 'priceToBook': 44.82666,\n",
       " 'lastFiscalYearEnd': 1727481600,\n",
       " 'nextFiscalYearEnd': 1759017600,\n",
       " 'mostRecentQuarter': 1743206400,\n",
       " 'earningsQuarterlyGrowth': 0.048,\n",
       " 'netIncomeToCommon': 97294000128,\n",
       " 'trailingEps': 6.41,\n",
       " 'forwardEps': 8.31,\n",
       " 'lastSplitFactor': '4:1',\n",
       " 'lastSplitDate': 1598832000,\n",
       " 'enterpriseToRevenue': 7.601,\n",
       " 'enterpriseToEbitda': 21.914,\n",
       " '52WeekChange': 0.04772854,\n",
       " 'SandP52WeekChange': 0.12473929,\n",
       " 'lastDividendValue': 0.26,\n",
       " 'lastDividendDate': 1747008000,\n",
       " 'quoteType': 'EQUITY',\n",
       " 'currentPrice': 200.42,\n",
       " 'targetHighPrice': 300.0,\n",
       " 'targetLowPrice': 170.62,\n",
       " 'targetMeanPrice': 228.75928,\n",
       " 'targetMedianPrice': 230.0,\n",
       " 'recommendationMean': 2.08696,\n",
       " 'recommendationKey': 'buy',\n",
       " 'numberOfAnalystOpinions': 41,\n",
       " 'totalCash': 48497999872,\n",
       " 'totalCashPerShare': 3.247,\n",
       " 'ebitda': 138865999872,\n",
       " 'totalDebt': 98186002432,\n",
       " 'quickRatio': 0.68,\n",
       " 'currentRatio': 0.821,\n",
       " 'totalRevenue': 400366010368,\n",
       " 'debtToEquity': 146.994,\n",
       " 'revenuePerShare': 26.455,\n",
       " 'returnOnAssets': 0.23809999,\n",
       " 'returnOnEquity': 1.38015,\n",
       " 'grossProfits': 186699005952,\n",
       " 'freeCashflow': 97251500032,\n",
       " 'operatingCashflow': 109555998720,\n",
       " 'earningsGrowth': 0.078,\n",
       " 'revenueGrowth': 0.051,\n",
       " 'grossMargins': 0.46632,\n",
       " 'ebitdaMargins': 0.34685,\n",
       " 'operatingMargins': 0.31028998,\n",
       " 'financialCurrency': 'USD',\n",
       " 'symbol': 'AAPL',\n",
       " 'language': 'en-US',\n",
       " 'region': 'US',\n",
       " 'typeDisp': 'Equity',\n",
       " 'quoteSourceName': 'Nasdaq Real Time Price',\n",
       " 'triggerable': True,\n",
       " 'customPriceAlertConfidence': 'HIGH',\n",
       " 'averageAnalystRating': '2.1 - Buy',\n",
       " 'cryptoTradeable': False,\n",
       " 'hasPrePostMarketData': True,\n",
       " 'firstTradeDateMilliseconds': 345479400000,\n",
       " 'postMarketChangePercent': 3.5468,\n",
       " 'postMarketPrice': 207.529,\n",
       " 'postMarketChange': 7.10851,\n",
       " 'regularMarketChange': 0.209991,\n",
       " 'regularMarketDayRange': '199.9 - 202.73',\n",
       " 'fullExchangeName': 'NasdaqGS',\n",
       " 'averageDailyVolume3Month': 62197668,\n",
       " 'fiftyTwoWeekLowChange': 31.209991,\n",
       " 'fiftyTwoWeekLowChangePercent': 0.1844453,\n",
       " 'fiftyTwoWeekRange': '169.21 - 260.1',\n",
       " 'fiftyTwoWeekHighChange': -59.680008,\n",
       " 'fiftyTwoWeekHighChangePercent': -0.22945024,\n",
       " 'fiftyTwoWeekChangePercent': 4.772854,\n",
       " 'dividendDate': 1747267200,\n",
       " 'earningsTimestamp': 1746131400,\n",
       " 'earningsTimestampStart': 1753873140,\n",
       " 'earningsTimestampEnd': 1754308800,\n",
       " 'earningsCallTimestampStart': 1746133200,\n",
       " 'earningsCallTimestampEnd': 1746133200,\n",
       " 'isEarningsDateEstimate': True,\n",
       " 'epsTrailingTwelveMonths': 6.41,\n",
       " 'epsForward': 8.31,\n",
       " 'epsCurrentYear': 7.19127,\n",
       " 'priceEpsCurrentYear': 27.869904,\n",
       " 'fiftyDayAverageChange': -5.5227966,\n",
       " 'fiftyDayAverageChangePercent': -0.02681714,\n",
       " 'twoHundredDayAverageChange': -25.3992,\n",
       " 'twoHundredDayAverageChangePercent': -0.11247583,\n",
       " 'sourceInterval': 15,\n",
       " 'exchangeDataDelayedBy': 0,\n",
       " 'shortName': 'Apple Inc.',\n",
       " 'longName': 'Apple Inc.',\n",
       " 'marketState': 'PREPRE',\n",
       " 'corporateActions': [],\n",
       " 'postMarketTime': 1748476799,\n",
       " 'regularMarketTime': 1748462401,\n",
       " 'exchange': 'NMS',\n",
       " 'messageBoardId': 'finmb_24937',\n",
       " 'exchangeTimezoneName': 'America/New_York',\n",
       " 'exchangeTimezoneShortName': 'EDT',\n",
       " 'gmtOffSetMilliseconds': -14400000,\n",
       " 'market': 'us_market',\n",
       " 'esgPopulated': False,\n",
       " 'regularMarketChangePercent': 0.104886,\n",
       " 'regularMarketPrice': 200.42,\n",
       " 'displayName': 'Apple',\n",
       " 'trailingPegRatio': 2.0372}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import yfinance as yf\n",
    "\n",
    "apple= yf.Ticker(\"AAPL\")\n",
    "apple.info\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "48b8f1d6",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "                                 Open        High         Low       Close  \\\n",
       "Date                                                                        \n",
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       "2025-05-05 00:00:00-04:00  202.834025  203.832716  197.950430  198.629532   \n",
       "\n",
       "                              Volume  Dividends  Stock Splits  \n",
       "Date                                                           \n",
       "2025-04-29 00:00:00-04:00   36827600        0.0           0.0  \n",
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 展示数据集前5行\n",
    "data = apple.history()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5f6e779a",
   "metadata": {},
   "outputs": [
    {
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       "                                 Open        High         Low       Close  \\\n",
       "Date                                                                        \n",
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       "2025-05-22 00:00:00-04:00  200.710007  202.750000  199.699997  201.360001   \n",
       "2025-05-23 00:00:00-04:00  193.669998  197.699997  193.460007  195.270004   \n",
       "2025-05-27 00:00:00-04:00  198.300003  200.740005  197.429993  200.210007   \n",
       "2025-05-28 00:00:00-04:00  200.589996  202.729996  199.899994  200.419998   \n",
       "\n",
       "                             Volume  Dividends  Stock Splits  \n",
       "Date                                                          \n",
       "2025-05-21 00:00:00-04:00  59211800        0.0           0.0  \n",
       "2025-05-22 00:00:00-04:00  46742400        0.0           0.0  \n",
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      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 展示数据集后5行 \n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "23e8b4be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化dataframe\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "data.plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b36170f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "prices=data['Close']\n",
    "volumes=data['Volume']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9f428948",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2025-04-28 00:00:00-04:00    209.864792\n",
       "2025-04-29 00:00:00-04:00    210.933395\n",
       "2025-04-30 00:00:00-04:00    212.221710\n",
       "2025-05-01 00:00:00-04:00    213.040634\n",
       "2025-05-02 00:00:00-04:00    205.081070\n",
       "Name: Close, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4fc2f450",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2025-05-21 00:00:00-04:00    59211800\n",
       "2025-05-22 00:00:00-04:00    46742400\n",
       "2025-05-23 00:00:00-04:00    78432900\n",
       "2025-05-27 00:00:00-04:00    56229000\n",
       "2025-05-28 00:00:00-04:00    10912153\n",
       "Name: Volume, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "volumes.tail()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f218740e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(volumes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7de5756",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top=plt.subplot2grid((4,4),(0,0),rowspan=3, colspan=4)\n",
    "top.plot(prices.index, prices, label='Close')\n",
    "plt.title('Apple Close Price from 20250428-20250828')\n",
    "plt.legend(loc=2)\n",
    "\n",
    "bottom=plt.subplot2grid((4,4),(3,0),rowspan=1, colspan=4)\n",
    "bottom.bar(volumes.index, volumes)\n",
    "plt.title('Apple Daily Trading volume')\n",
    "\n",
    "# 设置图形尺寸\n",
    "plt.gcf().set_size_inches(12,8)\n",
    "# 设置子图间距\n",
    "plt.subplots_adjust(hspace=0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "334195b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from mpl_finance import candlestick_ohlc\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.pyplot as plt\n",
    "import yfinance as yf\n",
    "\n",
    "apple=yf.Ticker('AAPL')\n",
    "df_subset=apple.history()\n",
    "df_subset['Date']=df_subset.index.map(mdates.date2num)\n",
    "df_ohlc=df_subset[['Date','Open','High','Low','Close']]\n",
    "\n",
    "figure,ax = plt.subplots(figsize = (8,4))\n",
    "formatter = mdates.DateFormatter('%Y-%m-%d')\n",
    "ax.xaxis.set_major_formatter(formatter)\n",
    "candlestick_ohlc(ax, df_ohlc.values, width=0.8, colorup='green', colordown='red')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5f446cf8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_subset=apple.history()\n",
    "df_close=df_subset[['Close']]\n",
    "daily_changes = df_close.pct_change(periods=1)\n",
    "daily_changes.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "53fc4448",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Date'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cumsum=df_close.cumsum()\n",
    "df_cumsum.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "03b3180b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: title={'center': 'Close'}>]], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_close.hist(bins=50, figsize=(8,4))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
